Tellu: an object detector algorithm for automatic classification of intestinal organoids.

Intestinal epithelial organoids recapitulate many of the in vivo features of the intestinal epithelium, thus representing excellent research models. Morphology of the organoids based on light microscope images is used as a proxy to assess the biological state of the intestinal epithelium. Currently, organoid classification is manual and therefore subjective and time-consuming, hampering large-scale quantitative analyses. Here we describe Tellu, an object detector algorithm trained to classify cultured intestinal organoids. Tellu was trained by manual annotation of >20000 intestinal organoids to identify cystic non-budding organoids, early organoids, late organoids, and spheroids. Tellu can also be used to quantify relative organoid size. Tellu classifies intestinal organoids to these four subclasses with accuracy comparable to trained scientists but significantly faster and without bias. Tellu is provided as an open, user-friendly online tool to benefit the increasing number of investigations using organoids through fast and unbiased organoid morphology and size analysis.